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University of San Francisco - College of Arts & Sciences M.S. in Data Science
University of San Francisco - College of Arts & Sciences

M.S. in Data Science

San Francisco, USA

1 Years

English

Full time

Request application deadline *

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USD 39,840 / per year **

On-Campus

* our early application date for priority scholarship consideration is December 5. The final application date is March 1

** tuition costs per year are estimates only; costs may vary based on actual enrollment in classes

Introduction

USF’s one-year Master of Science in Data Science (MSDS) program delivers a rigorous curriculum focused on mathematical and computational techniques in the emerging field of data science. The curriculum emphasizes the careful formulation of business problems, selecting effective analytical techniques to address those problems, and communicating solutions in a clear and creative fashion.

Over 90 percent of all graduates since the program's inception in 2012 received an offer of employment within three months of graduation at companies including Amazon, Apple, Facebook, LinkedIn, Lyft, Zillow, Twitch, Tesla, Microsoft, Pinterest, and Visa.

A Technically Challenging Curriculum

The program's challenging curriculum features seven-week courses designed specifically for our students — they're not offered in other programs or departments. Students master subjects from computer science, statistics, and management such as regression, web scraping, SQL and NoSQL database management, natural language processing, business communications, machine learning, cluster analysis, application development, and interviewing skills. Students primarily use the Python programming language in their classes and learn how to effectively use distributed computing technology such as MapReduce, Hadoop, and Spark, and become intimately familiar with cloud technology such as Amazon Web Services. Students have access to the Data Institute's GPU computing cluster.

Faculty

Our faculty represent the fundamental multidisciplinary nature of the big data industry. They’re traditional academics and data scientists actively working in the field, using real industry experience to inspire their instruction. Their areas of expertise include deep learning, natural language processing, databases, statistical modeling, network analytics, algorithms, unsupervised learning, machine learning, optimization, health analytics, and signal processing.

Admissions

Curriculum

Program Outcome

Scholarships and Funding

Career Opportunities

English Language Requirements

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About the School

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